title: Stabilizing gene regulatory networks through feedforward loops.
abstract: The global dynamics of gene regulatory networks are known to show robustness to perturbations in the form of intrinsic and extrinsic noise, as well as mutations of individual genes. One molecular mechanism underlying this robustness has been identified as the action of so-called microRNAs that operate via feedforward loops. We present results of a computational study, using the modeling framework of stochastic Boolean networks, which explores the role that such network motifs play in stabilizing global dynamics. The paper introduces a new measure for the stability of stochastic networks. The results show that certain types of feedforward loops do indeed buffer the network against stochastic effects.
authors.affiliation: Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia 24061, USA. claus89@vt.edu
authors.forename: C
authors.initials: C
authors.lastname: Kadelka
authors.forename: D
authors.initials: D
authors.lastname: Murrugarra
authors.forename: R
authors.initials: R
authors.lastname: Laubenbacher
mesh_terms: D000818:Animals; D025461:Feedback, Physiological; D053263:Gene Regulatory Networks; D035683:MicroRNAs / Q000235:genetics / Q000378:metabolism; D013269:Stochastic Processes; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D035683:MicroRNAs; D014157:Transcription Factors